Ivanenko, Victor and Pasichnichenko, Illia (2016): Expected utility for nonstochastic risk.
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Abstract
The world of random phenomena exceeds the domain of the classical probability theory. In the general case the description of randomness requires a specific set of probability distributions (which is called statistical regularity) rather than a singe distribution. Such statistical regularity arises as a limit of relative frequencies. This approach to randomness allows to generalize the expected utility theory in order to cover the decision problems under nonstochastic random events. Applying the von Neumann-Morgenstern utility theorem, we derive the maxmin expected utility representation for statistical regularities. The derivation is based on the axiom of the preference for stochastic risk, i.e. the decision maker wishes to reduce the set of probability distributions to a single one.
Item Type: | MPRA Paper |
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Original Title: | Expected utility for nonstochastic risk |
Language: | English |
Keywords: | expected utility, risk, mass phenomena, statistical regularity, nonstochastic randomness, multiple prior |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D81 - Criteria for Decision-Making under Risk and Uncertainty |
Item ID: | 70433 |
Depositing User: | Illia Pasichnichenko |
Date Deposited: | 03 Apr 2016 16:03 |
Last Modified: | 27 Sep 2019 13:52 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/70433 |
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